Relationship between trimethylamine N-oxide and the risk of hypertension in patients with cardiovascular disease: A meta-analysis and dose-response relationship analysis.

BACKGROUND: The gut microbiota-dependent metabolite trimethylamine N-oxide (TMAO) has recently been recognized to be one of the risk factors for cardiovascular disease (CVD). However, there is a scarcity of data on the relationship between circulating TMAO levels and hypertension in patients with CVD. Meta analysis and a dose-response relationship were used in this study to assess the relationship between circulating trimethylamine N-oxide levels and the risk of hypertension in patients with CVD. METHODS: CNKI, Wanfang Database, Pubmed, Embase, Cochrane Library, and Web of Science were searched up to June 01, 2023. Meta-analysis and dose-response analysis of relative risk data from prospective cohort studies reporting on the relationship between circulating TMAO levels and hypertension risk in patients with CVD were conducted. RESULTS: Fifteen studies with a total of 15,498 patients were included in the present meta-analysis. Compared with a lower circulating TMAO level, a higher TMAO level was associated with a higher risk of hypertension in patients with CVD (RR = 1.14,95%CI (1.08, 1.20)). And the higher the TMAO level, the greater the risk of hypertension. The dose-response analysis revealed a linear dose-response relationship between circulating TMAO levels and the risk of hypertension in patients with CVD. The risk of hypertension increased by 1.014% when the circulating TMAO level increased by 1 µ mol/L. CONCLUSION: In patients with CVD, the level of circulating TMAO is significantly related to the risk of hypertension. The risk of hypertension increased by 1.014% for every 1 µ mol/L increase in circulating TMAO levels.

Predicting energy use in construction using Extreme Gradient Boosting.

Annual increases in global energy consumption are an unavoidable consequence of a growing global economy and population. Among different sectors, the construction industry consumes an average of 20.1% of the world's total energy. Therefore, exploring methods for estimating the amount of energy used is critical. There are several approaches that have been developed to address this issue. The proposed methods are expected to contribute to energy savings as well as reduce the risks of global warming. There are diverse types of computational approaches to predicting energy use. These existing approaches belong to the statistics-based, engineering-based, and machine learning-based categories. Machine learning-based frameworks showed better performance compared to these other approaches. In our study, we proposed using Extreme Gradient Boosting (XGB), a tree-based ensemble learning algorithm, to tackle the issue. We used a dataset containing energy consumption hourly recorded in an office building in Shanghai, China, from January 1, 2015, to December 31, 2016. The experimental results demonstrated that the XGB model developed using both historical and date features worked better than those developed using only one type of feature. The best-performing model achieved RMSE and MAPE values of 109.00 and 0.24, respectively.

In Situ Fabrication of N-Doped ZnS/ZnO Composition for Enhanced Visible-Light Photocatalytic H2 Evolution Activity.

For achieving the goal of peaking carbon dioxide emissions and achieving carbon neutrality, developing hydrogen energy, the green and clean energy, shows a promising perspective for solving the energy and ecological issues. Herein, firstly, we used the hydrothermal method to synthesize the ZnS(en)0.5 as the precursor. Then, ZnS/ZnO composite was obtained by the in situ transformation of ZnS(en)0.5 with heat treatment under air atmosphere. The composition, optical property, morphology, and structural properties of the composite were characterized by X-ray photoemission spectroscopy (XPS), Ultraviolet-visible absorption spectra (Uv-vis Abs), Scanning electron microscopy (SEM) and Transmission electron microscopy image (TEM). Moreover, the content of ZnO in ZnS/ZnO was controlled via adjustment of the calcination times. The visible-light response of ZnS/ZnO originated from the in situ doping of N during the transformation of ZnS(en)0.5 to ZnS/ZnO under heat treatment, which was verified well by XPS. Photocatalytic hydrogen evolution experiments demonstrated that the sample of ZnS/ZnO-0.5 h with 6.9 wt% of ZnO had the best H2 evolution activity (1790 µmol/h/g) under visible light irradiation (λ > 400 nm), about 7.0 and 12.3 times that of the pure ZnS and ZnO, respectively. The enhanced activities of the ZnS/ZnO composites were ascribed to the intimated hetero-interface between components and efficient transfer of photo-generated electrons from ZnS to ZnO.

pH-responsive zwitterionic polypeptide as a platform for anti-tumor drug delivery.

In this paper, a doxorubicin delivery system is reported based on a pH-responsive zwitterionic polypeptide derivative. To improve the anti-protein-fouling capacity, the poly(amino acid) was modified by grafting short-chain zwitterions via aminolysis reaction of polysuccinimide with l-lysine. As a result, both positively and negatively charged moieties were introduced onto the same side chain in a simultaneous fashion, providing a nano-scale homogenous mixture of balanced charges. The zwitterionic side chains serve as hydrophilic segments in the copolymer and feature excellent resistance to nonspecific protein adsorption. Doxorubicin was chemically grafted onto the poly(amino acid) moiety through acid-labile hydrazone linkages, providing removable hydrophobic segments and driving the polymer self-assembly. Free doxorubicin could be encapsulated into the self-assembled micelles via hydrophobic interactions and molecular π-π stacking. The results obtained show that the drug loaded nanoparticles exhibit excellent stabilities in protein solutions at pH=7.4 and significantly enhanced drug release characteristics under acidic conditions. The cytotoxicity characteristics of the zwitterionic copolymer and drug-loaded nanoparticles at different pH values were investigated in vitro and feature an excellent biocompatibility and anti-cancer activity, respectively.

PH responsive polypeptide based polymeric micelles for anticancer drug delivery.

A pH-responsive polymeric micelle based on poly(aspartamide) derivative was explored as an efficient acid-triggered anticancer drug delivery system. Poly(α,ß-l-asparthydrazide) (PAHy) was prepared by aminolysis reaction of polysuccinimide with hydrazine hydrate. Poly(ethylene glycol) and aliphatic chain (C18) were conjugated onto PAHy to afford an amphiphilic copolymer with acid-liable hydrazone bonds. The structure of the resulting copolymer and its self-assembled micelles were confirmed by (1) H NMR, FTIR, DLS, and TEM. Furthermore, doxorubicin (DOX) was loaded into the polymeric micelles via the hydrophobic interaction between the C18 group and DOX molecules, and the π-π staking between the hydrazone conjugated DOX and free DOX molecules. Results showed that the DOX loaded nanoparticle (NP) was relatively stable under physiological conditions, while the DOX was quickly released in response to acidity due to the shedding of mPEG shells and dissociating of C18 segments because of the pH-cleavage of intermediate hydrazone bonds. In addition, the DOX loaded micelles presented a high cytotoxic activity against tumor cells in vitro. This pH responsive NP has appeared highly promising for the targeted intracellular delivery of hydrophobic chemotherapeutics in cancer therapy.